This document summarizes several remote sensing technologies used for environmental monitoring, including video, LIDAR, hyperspectral sensing, and INSAR. Video can be integrated with GPS to monitor environments. LIDAR uses light to map underwater environments up to 60m deep or 30 sq km areas on land with accuracy of 3m horizontally and 0.15m vertically. Hyperspectral sensors can identify vegetation and minerals by their light absorption characteristics across 288 wavelengths. INSAR uses phase differences from satellites to measure ground displacement with millimeter accuracy, useful for monitoring earthquakes, subsidence, and dam movement.
Summary of DART Electromagnetic Methodology 100111
Flood modelling and management using remote sensing technologies
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14. Phase changes original ground position displaced ground position satellite position at first acquisition satellite position at second acquisition Different signal path lengths means difference in signal phase Slide courtesy of NPA associates, UK
Used from the air can detail electrical lines or....
Used from the air can detail electrical lines or....
CASI principle of operation The system has a "pushbroom" configuration, ie the full swath width is imaged instantaneously in a large number of spectral wavebands (up to 288) covering the visible and near infra-red regions of the spectrum between 430nm and 900nm. This can be used to construct hyperspectral image data sets for detailed studies of ground or water targets. Spatial resolution can be varied from one to ten metres, and is governed by the flying altitude Examples of CASI Mapping and classification of wetland vegetation Mapping and classification of benthic habitat Identifying mineral composites Identifying specific agricultural crops Mapping bathymetry in near-shore environments Mapping the benthic community in near-shore environments Identifying forest structure and composition Identifying soil types
Earthquake in California 1999
Measure impact of flooding, in this case 0.25m increments.
Earthquake in California 1999
Radar comparisons of before and after calculated as phase difference and illustrated by crests, each 25mm in movement.
Total movement is shown as contour map.
Total movement is shown as contour map.
Orthophotomap
Orthophotomap
Trend towards countrywide data sets – driven by insurance industry in GB as well as the EA’s obligation to flood management and monitoring Increasing use of space borne sensors Increasing accuracy of geospatial information
Trend towards countrywide data sets – driven by insurance industry in GB as well as the EA’s obligation to flood management and monitoring Increasing use of space borne sensors Increasing accuracy of geospatial information
Trend towards countrywide data sets – driven by insurance industry in GB as well as the EA’s obligation to flood management and monitoring Increasing use of space borne sensors Increasing accuracy of geospatial information
Trend towards countrywide data sets – driven by insurance industry in GB as well as the EA’s obligation to flood management and monitoring Increasing use of space borne sensors Increasing accuracy of geospatial information